I'm building an algorithmic trading business. I'd be grateful for informed comments and opinions on my trading strategy search methodology.
Develop (profitable!) fully automated intra-day trading strategies.
I'm focusing on FX futures and equity index futures on CME and LIFFE. Becuase:
- I know these markets best
- I can get roundtrip times of 10s ms
- Futures margin means big leverage for my small account
I'm buying in Level 1 tickdata from the exchanges. I don't think level 2 data would add anything because I wont have low enough latency to make use of it. A typical contract might have 1M data points per day.
I have a bias towards machine learning specifically SVM/R. My plan goes like this
- Choose an instrument and forecast horizon (5-120 seconds)
- Assembly a large stable of features e.g.
- Resampled lagged time series and returns
- Wavelet transform of the above
- Measures of information entropy
- Some indicators from Operators on Inhomogeneous Time Series (This is 11 years old now but I've yet to see anything that meaningfully expands on it)
- If can hold down the vomit some 'Traditional Technical Analysis' indicators
- Choose a subset of features with genetic search. The objective function is the MSE of the n-fold SVM cross validation
- Build the final SVM with the best parameter selection.
- Hope that the highest confidence predictions form the basis of a profitable trading strategy
In your experience do you think a strategy developed like this can hope to make money on liquid equity index and FX futures? If not why not?